A grip force model for the da Vinci end-effector to predict a compensation force

Area of Science:

• Robotics
• Surgical Technology
• Biomechanics

Background:

• Current da Vinci robot systems exhibit variable grip forces due to EndoWrist posture.
• This variability poses a risk of inconsistent force application to delicate tissues.

Purpose of the Study:

• To develop a torque transfer system (TTS) for measuring grip forces.
• To create and validate a preliminary model of the EndoWrist Inner Mechanism Model (EIMM).
• To analyze grip force variations across different EndoWrist postures.

Main Methods:

• Developed a TTS to measure EndoWrist grip forces, posture angles, and transferred torque.
• Collected grip force data from three EndoWrists across 27 distinct postures.
• Constructed the EIMM using posture angles as input and grip forces as output.
• Validated the EIMM by comparing its predicted grip forces with actual measurements.

Main Results:

• Significant diversity in mean grip forces was observed across different postures (1.84x to 3.37x variation).
• The EIMM accurately predicted grip force values, validating the proposed model.
• Demonstrated that the same applied force by a surgeon results in substantially different grip forces depending on posture.

Conclusions:

• Surgeons can benefit from understanding actual grip forces and robotic system mechanics.
• The EIMM provides a baseline for designing force-feedback systems in surgical robots.
• Accurate grip force measurement and modeling are vital for preventing tissue injury in robotic surgery.